Encoding invisible electronic information in a printed document

ABSTRACT

A printed image can be redundantly encoded by printing a visible image using a colorant with a luminance that contrasts with that of the output sheet and printing a redundant image using a colorant with a luminance that varies only slightly from that of the output sheet. Accordingly, the visible image can be easily read by a user while the redundant image is substantially invisible to the human eye at normal-reading distances, yet capable of being captured by a conventional digital scanner. In one aspect, redundantly encoded images may be printed on a white background, with visible images printed in black text and redundant images printed in blue in content regions of the visible image and in yellow in its background regions.

This is a continuation in part application of co-pending U.S. patentapplication Ser. No. 10/951,394 Entitled “Encoding Invisible ElectronicInformation in a Printed Document” filed Sep. 28, 2004, which isassigned to the present assignee.

BACKGROUND

It is often useful to recover the image that was originally printed on ahardcopy document later became altered or damaged. For example, it isoften difficult to recreate information that is printed on financial,legal, medical and government, but it is essential that those who relyupon these types of information to know that the information theyreceive is accurate and complete. Thus, it would be beneficial toprovide a way to view the original version of an image that is presentedon a printed document, to confirm it accuracy and when necessary, torecover data from a document that has been damaged.

Known image processing methods use “glyphs,” i.e., graphical indiciathat are used to encode digital information, to print duplicatedversions of a digital image on a single document. Unfortunately, glyphsare highly visible and thus, they often detract from the visualappearance of the document. Magnetic inks, gloss marks and othersubstances that are much less visible are also available, but the costsof providing the equipment that is required to capture the data oftenrenders the use of those substances impractical.

Available software programs can highlight changes in electronic versionsof a modified image for comparison purposes. Those programs cannot,however, identify and highlight changes that are made to printed data.It is also relatively easy to deliver editing history withelectronically stored documents. Unfortunately that information is lostwhen the document is printed, even if the hardcopy document is scannedand the image is returned to electronic storage.

Accordingly, it would be advantageous to be able to redundantly encodeimage data on a hardcopy document, to do so without altering the visualappearance of the document and to enable the redundant versions of theimage to maintain their association as the hardcopy document isdigitally captured, processed and printed.

Prior Art

U.S. Pat. No. 5,835,638 discloses a method and apparatus for comparingsymbols extracted from binary images of text for classifying intoequivalence classes using a Hausdorff-like method for comparing symbolsfor similarity. When a symbol contained in a bitmap A is compared to asymbol contained in a bitmap B, it is determined whether or not thesymbol in bitmap B fits within a tolerance into a dilated representationof the symbol in bitmap A with no excessive density of errors andwhether the symbol in bitmap A fits within a tolerance into a dilatedrepresentation of the symbol in bitmap B with no excessive density oferrors. If both tests are passed, an error density check is performed todetermine a match.

U.S. Pat. No. 5,539,841 discloses a method for comparing two imagesections consisting of a plurality of image signals, or pixels, whereeach image section represents a token (e.g., character, symbol, glyph,string of components, or similar units of semantic understanding), inorder to identify when similar tokens are present within the imagesections.

SUMMARY

Aspects disclosed herein provide a digital printing system that includesan image processor configured to generate binary printer signals thatrepresent an encoded image inside a scan image, wherein the encodedimage includes a visible representation of a presented image and has asubstantially invisible representation of an original image printedamong the presented image; a print channel configured to receive thebinary printer signals from the image processor as a plurality ofseparations; an encoded image analyzer configured to obtain an encodingtransformation function used to position pixels corresponding to thesubstantially invisible original image representation among the originalimage; an original image location identifier that identifies pixels inthe scan image that correspond to locations of the substantiallyinvisible original image representation and applies a decodingtransformation function to the substantially invisible original imagerepresentation corresponding pixels; an original image recovery deviceconfigured to assign a selected grayscale value to each pixel of thesubstantially invisible original image representation identified by thedecoding transformation function; and an output generator configured togenerate a visible representation of the original image.

In one aspect, a method includes digitally capturing grayscale pixelsthat represent an encoded image inside a scan image, wherein the encodedimage includes a visible representation of a presented image and has asubstantially invisible representation of an original image printedamong the presented image; identifying an encoding transformationfunction used to position pixels corresponding to the substantiallyinvisible original image representation among the original image;locating pixels in the scan image that correspond to locations of thesubstantially invisible original image representation; applying adecoding transformation function to the substantially invisible originalimage representation corresponding pixels to locate pixels correspondingto the original image; and assigning a selected grayscale value to eachof the original image corresponding pixels.

In another aspect, a method includes generating image data that providesa digital representation of an original image; providing an encodingtransformation function for positioning pixels of a substantiallyinvisible representation of the original image inside the originalimage; printing the original image an output copy sheet; and printingthe substantially invisible original image representation on the outputcopy sheet, with pixels of the substantially invisible original imagerepresentation dispersed among the original image.

In yet another aspect, a data encoder includes an input channelconfigured to receive pixel values that digitally represent an originalimage; a redundant image pixel selector configured to provide anencoding transformation function that maps pixels belonging to asubstantially invisible representation of the original image tocorresponding pixels in a visible representation of the original image;a visible image generator configured to print the visible original imagerepresentation on an output copy sheet using a colorant whose luminancevalue differs substantially from a luminance value of a print locationfor the visible image representation; and a redundant image generatorconfigured to print the substantially invisible original imagerepresentation using a colorant whose luminance value is substantiallythe same as a luminance value for a pixel identified by the encodingtransformation function.

In still another aspect, a data encoder includes an input channelconfigured to receive pixel values that digitally represent an originalimage; a redundant image pixel selector configured to provide anencoding transformation function that maps pixels belonging to asubstantially invisible representation of the original image tocorresponding pixels in a visible representation of the original image;a visible image generator configured to visibly display the visibleoriginal image representation in color whose luminance value differssubstantially from a luminance value of a region surrounding the visibleimage representation; and a redundant image generator configured todisplay the substantially invisible original image representation in acolor whose luminance value is substantially the same as a luminancevalue of a surrounding location.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified diagram showing the basic elements of a colordigital printer.

FIG. 2 is a simplified diagram showing the basic elements of a rasterinput scanner.

FIG. 3 is a block diagram of one exemplary embodiment of a halftoneprocessor that can be used to convert RGB input to CMYK output.

FIG. 4 is an example of a redundantly encoded image printed on ahardcopy document.

FIG. 5 shows an example of how pixels in a redundant image can be mappedto locations in a visibly presented image.

FIG. 6 is an example of a redundant image that includes registrationmarks.

FIG. 7 is a flow chart that illustrates a method of recovering anoriginal image from a redundantly encoded printed image.

FIG. 8 is a flow chart showing a method of deriving a transformationfunction

FIG. 9 is a flow chart showing a method of refining a transformationfunction such as that derived in the example of FIG. 8.

DETAILED DESCRIPTION

For a general understanding of the present invention, reference is madeto the drawings, where like reference numerals have been used throughoutto designate identical elements. In describing the present invention,“a” means “one or more” and a “plurality” means “more than one.” Thefollowing term(s) have also been used in the description:

“Data” refers to electronic signals that indicate or includeinformation. Data may exist in any physical form, includingelectromagnetic or other transmitted signals, signals that are stored inelectronic, magnetic, or other form or signals that are transitory orare in the process of being stored or transmitted.

“Viewable data” refers to data that typically can be perceived by thehuman visual system. In contrast, “substantially invisible data” is datathat present but is barely detectable or undetectable by the human eyeat a typical viewing distance.

An “image” is generally a pattern of physical light that may includecharacters, words, and text as well as other features such as graphics.An image is typically represented by a plurality of pixels that arearranged in scanlines.

An “input image” is an image that has been generated by an externalsource or process that is presented to the reference system forprocessing.

A “document” includes any medium that is capable of bearing a visibleimage.

An “original document” is a document that bears an input image.

A “separation” is a bitmap of image signals that is used to drive aprinter produce a monochromatic image.

A “pixel” is a digital signal that represents the optical density of theimage in a single separation at a discrete location.

A “color pixel” refers to the set of color densities of correspondingpixels in each separation.

“Grayscale” means having multiple intensity levels that correspond torespective optical density values. For a given device, the number ofavailable grayscale levels is determined by its bit depth. “Grayscalevalue” refers to the numerical value that represents a single intensitylevel in a range that varies between a minimum intensity level and amaximum intensity level. A grayscale value is assigned to each pixel ina digital image to indicate the optical density of the image at thecorresponding location.

“Color” is the appearance of an object as perceived by a viewerdepending upon the hue, brightness and saturation of light reflectedfrom the object.

A “color image” is an image formed by superimposing multiplemonochromatic separations, each of which reproduces a color of theimage.

A “neighborhood” is a group of pixels that lie adjacent to or surround areference pixel in an image. It is typically described by its size andshape.

“Resolution” is a number that describes pixels in an output device. Fora video display, resolution is typically expressed as the number ofpixels on the horizontal axis and the number of pixels on the verticalaxis. Printer resolution is often expressed in terms of “dots-per-inch”i.e., the number of drops of colorant that can be printed within an inchon the page, which is often, but not necessarily, the same in bothdirections.

A “redundantly encoded digital image” refers to data that provides adigital representation of the information that is required to reproducea human readable image.

There are many ways to digitally reproduce images. For example, digitalcameras, scanners and other image capture devices generate digitalreproductions of analog data and several available software applicationsenable users to create text and graphic images in digital format.Digital image data can also be received via electronic transmission andretrieved from storage. Regardless of how it is created, digitalinformation can be printed, transmitted and displayed by printers, videomonitors, fax machines and other output devices.

In a typical color system, color documents are represented by multipleseparations of grayscale image data, each of which provides the pixelsthat drive a printer to produce one layer of color in an image. Colorimages are formed by combining the optical density values forcorresponding pixels in respective separations. As illustrated in FIG.1, a digital printer 10 reproduces color images by processing binary“CMY” image data to generate multiple image separations that are used toprint cyan (C), magenta (M) and yellow (Y) colors-(and optionally andblack (K) color in lieu of or in addition to cyan, magenta and yellow)on an output sheet.

In one aspect, a digital printer 10 may include a raster output scanner(ROS) 12 that drives a modulated a light 14 in response to electronicsignals 18 that are independently generated by an image processor (IP)20 for the respective separations. Modulated light 14 exposes thesurface of a uniformly charged photoconductive imaging member 16 toachieve a set of subtractive latent images that are subsequentlydeveloped by depositing (K), C, M and Y colorants onto the chargeretaining locations. The developed images are then transferred to anoutput sheet in superimposed registration with one another and fused tothe sheet to form a color hardcopy document 50.

Each of the aforementioned colorants absorbs light in a limited spectralregion of the range of visible light; cyan colorant absorbs red light,i.e., prevents light having a wavelength of approximately 650 nm frombeing reflected from the image, magenta colorant absorbs green light(light having a wavelength of approximately 510 nm) and yellow colorantabsorbs blue light (light having a wavelength of approximately 475 nm).Black colorant absorbs all wavelengths of light and can be depositedonto the latent image rather than depositing all three colorants at thesame location.

Accordingly, all of the printable colors can be produced by combiningthe different colorants in various ratios. For example, to generate ablue region in a hardcopy image, relatively high amounts of colorantwill be deposited onto corresponding locations of the C and Mseparations, with little or no colorant deposited in the correspondinglocation of the Y separation. The cyan and magenta colorants will absorbthe red and green light and thus, only blue light will be reflected fromthe document and perceived by the viewer. In other words, the intensityof blue light that will be reflected from the image is controlled by theoutput of the channel of printer 10 that controls the deposit of yellowcolorant. Similarly, the intensity of red light that will be reflectedfrom the image is controlled by the output of the channel of printer 10that controls the deposit of cyan colorant and the intensity of greenlight is controlled by the output of the channel of printer 10 thatcontrols the deposit of magenta colorant.

Scanners, digital cameras and other devices that are capable ofgenerating digital image data reproduce color quite differently. Anexample of a raster input scanner (IIT) 30, one well known image capturedevice, is illustrated in FIG. 2. As shown IIT 30 may be mounted to amoving carriage assembly 34 and placed below a glass platen 32. A lamp36 illuminates an original document 50 that is positioned on platen 32and an image sensor 38, which is typically mounted to carriage 34, isplaced in relative motion with platen 32. Image sensor 38 includes aplurality of sensor elements that capture the image by detecting theintensity of light reflected from corresponding locations in the imageand storing it as a proportionate electrical charge. In the case of acolor image, the sensor elements separately detect red (R), green (G)and blue (B) components of visible light that are reflected from theimage. The analog charges for each color component are separatelyforwarded to IP 20, where they are quantized to generate grayscale pixelvalues in three overlapping R, G and B image data planes.

Since digital input and output devices generate and process datadifferently, the printing of scanned images usually requires some formof image processing. Turning to FIG. 3, IP 20 typically receives andprocesses the grayscale RGB image data 32 generated by IIT 30 andperforms several processes, one of which includes the conversion ofgrayscale RGB image data 32 to binary CMYK image data that is suitablefor driving printer 10.

The human vision system perceives color using a luminance channel andtwo opponent chrominance channels, one for detecting red-greenchrominance differences and one for detecting blue-yellow chrominancedifferences. As the goal is to generate CMYK data that will be perceivedby human observers as having colors that closely match those of theinput image, the conversion of RGB image data to CMYK image data ofteninvolves an intermediate conversion to device independentluminance-chrominance data, which simulates the way color is processedby the human eye. For example, LCrCb data describes each color in termsof its luminance (L), red-green chrominance (Cr) and blue-yellowchrominance (Cb). Luminance-chrominance data is forwarded to halftoneprocessing channels 24C, 24M, 24Y and 24K, where it is independentlyprocessed to generate binary data for each of the C, M, Y and Kseparations. The CMYK image data is output over channels 26C, 26M, 26Yand 26K that are used to deposit colorants in each of the C, M, Y and Kseparations.

The human eye is much more sensitive to overall changes in luminance(i.e., brightness) than it is to changes in chrominance in small objectsor areas. Accordingly, images are typically printed on output mediausing colorants that have dissimilar luminance values. For example, manyimages are generated by printing black colorant on a white background.In a digital system that describes color values in 8-bit words, whitehas a grayscale value of R=255, G=255, B=255, which translates to aluminance-chrominance value of L=255, Cr=128, Cb=128 and black has agrayscale value of R=0, G=0, B-0, which translates to aluminance-chrominance value of L=0, Cr=128, Cb=128. Since the luminancevariation between the colorant and background media is high (and in factin this case, represents the maximum possible difference), the imagethat is displayed is easily detected.

If the colorant used to print the image instead had a luminance valuethat was similar to that of the background media, the image would besubstantially invisible to the human eye so long as the image wassufficiently small. For example, yellow has a grayscale value of R=255,G=255, B=0, which translates to a luminance-chrominance value of L=225,Cr=149, Cb=1. Since the luminance of yellow and white are almost thesame, a yellow image printed on a white background would be virtuallyundetectable. Similarly, blue has a grayscale value of R=0, G=0, B=255,which translates to a luminance-chrominance value of L=29, Cr=108,Cb=255, which varies only slightly from that of black and thus, a tinyblue image printed on a black background would also be virtuallyundetectable. While small luminance variations are likely to beundetected by the human eye, they are typically captured by a digitalscanner.

Turning to FIG. 4, present systems and methods can be used to generate aredundantly encoded image 55 that includes a visible image with asubstantially invisible duplicate (a “redundant image”) 44 of anoriginal image printed inside. When initially created, the visibleportion of redundantly encoded image 55 is an original image 42. Butlike any printed image, redundantly encoded images 55 can be printed,digitally captured and perhaps modified by those who receive it.However, the presence of redundant image 44 enables a redundantlyencoded image 55 that is digitally captured to be processed to recreateoriginal image 42. Accordingly, present systems and methods allow thosewho receive printed images to determine whether the visible image thathas been presented is the same as original image 42 and to recover anoriginal image 42 from a modified version. Present systems and methodscan also be used to recapture original images 42 from a hardcopydocument 50 that has been damaged.

Like original image 42, redundant image 44 is generated by depositing acolorant onto an output sheet in response to signals that are generatedby IP 20. However, unlike original image 42, redundant image 44 isprinted in a color with a luminance value that closely matches that ofthe output sheet. Redundant image 44 is typically generated bytransmitting image signals 18 to printer 10 over a halftone processingchannel that will cause a colorant with a selected luminance to bedeposited onto the output sheet. More specifically, the luminance valuefor the color of redundant image 44 will closely match the luminancevalue for the color of the output sheet. In such cases, redundant image44 will be substantially invisible to the human eye, but still capturedby IIT 30. Since the same set of image data signals is used to generateboth original image 42 and redundant image 44, the image data that iscaptured from redundant image 44 can be used to recreate original image42.

It is quite common for an IP 20 to transmit image data 18 to printer 10over the channel corresponding to black colorant to black print a blackoriginal image 42 on a white output sheet. In one aspect, a redundantimage 44 may be generated by retransmitting the image data 18 over thechannel corresponding to yellow colorant to print a yellow redundantimage 44 on the same output sheet. Accordingly, only blue and yellowlight will be reflected from the regions of document 50 where redundantimage 44 is displayed. Further, if redundant image 44 is generated byprinting the image in yellow in background regions of original image 42and in blue in content regions, the small luminance differences betweenthe yellow image and white background and between the blue image andblack content will render the entire redundant image 44 substantiallyinvisible to the human eye. Accordingly, redundant image pixels can beprinted in both background regions (i.e., where the grayscale value isequal to the maximum available value) and content regions (i.e., wherethe grayscale value is less than the maximum value) of original image42.

Notably, present systems and methods are not limited to encoding binaryimage data. The pixel value for each pixel in a grayscale redundantimage 44 can be represented as:R(i′, j′)=W(i, j)G(i′, j′)=W(i, j)B(i′, j′)=W(i, j)*W(i′, j′)+(1−W(i, j))*(1−W(i′, j′)),

where W=1 at white pixels; W=0 at black pixels; pixels in original image42 are located in positions (i, j); pixels in redundant image 44 arelocated in positions (i′, j′); W(i, j) is the grayscale value at pixel(i, j); and the red, green and blue output values at pixels (i′, j′) areR(i′, j′), G(i′, j′) and B(i′, j′).

In one aspect, the print locations for pixels in redundant image 44 aremodified before they are printed in original image 42. Morespecifically, in one aspect, the coordinates for redundant image pixelsare scrambled relative to the coordinates of the corresponding originalimage pixels. Accordingly, redundant image 44 is scattered across thesurface of the original image, with each pixel positioned in a locationthat is selected using an encoding transformation function (T_(E)). Whenthe redundant information is scattered across the original image, theoriginal data is much more likely to be recoverable from a document 50that has been damaged or altered.

In one aspect, pixels in redundant image 44 are located by measuring theintensity of light reflected from the image that has a selected color.In the example described above, redundant image 44 includes those pixelswhere the color value has a yellow-blue intensity (YB) that exceeds apredetermined threshold (t). That is, YB=|B−(R+G)/2|−R−G|>t. In otherwords, a given pixel is identified as belonging to redundant image 44when its color value is dominated by signals that correspond to theblue-yellow chrominance channel (Cb).

Each pixel in original image 42 is identified by coordinates (i, j) thatspecify its location inside the image in the fast scan (i) and slow scan(j) direction. Accordingly, each pixel within the same line will havethe same “j” coordinate and pixels that are aligned in the same columnin different scanlines will have the same “i” coordinate. In one aspect,the location of each pixel in redundant image 44 that represents acontent location in original image 42 can be identified using anencoding transformation function (T_(E)) that modifies the coordinatesof the corresponding original image 42 pixel.

An encoding transformation function that can be used to map the originalimage to corresponding pixels in a redundant image 44 is illustrated inFIG. 5. In the example shown, redundantly encoded image 55 has beenencoded in the original image using the function: T_(E)(i′,j′)=[i′=reversebits(i+j); j′=reversebits(j+i′)]. The encoding functionof this example first adds the relevant coordinates (i.e., i+j or i+j′).The addition is done modulo the image size, so for an image size that isa power of two this drops the first half of the bits in the resultingsum and the reversebits function reverses the order of the remainingbits. The coordinates (i, j) for each pixel location in the 4×4 blockare displayed in bold text at the top of each box along with thecorresponding binary value. The coordinates (i′, j′) for thecorresponding locations selected by the transformation function aredisplayed in outlined text at the top of each box with the correspondingbinary value. Arrows are also provided to show the correspondencebetween pixels in the original redundant images.

In an original image 42 that has content placed, for example, at thepixels in locations (3, 0) and (1, 3) and nothing placed at the pixel inlocation (2, 0), redundant image 44 would be printed at locations (1, 3)and (2, 0), which correspond to original image pixels (3, 0) and (1, 3)respectively. Location (3, 1), (2, 0), which correspond to originalimage pixel (2, 0) would not display any redundant image data.Accordingly, both original image 42 and redundant image 44 will bedisplayed at the pixel at location (1, 3) and that location of redundantimage 44 would be printed in blue. Since the redundant image pixelprinted at location (2, 0) is in the background of original image 42,redundant image 44 will be printed in yellow at that location.

It is noted that redundant image 44 and original image 42 do not have tobe printed at the same resolution. For example, on some occasions,redundant image 44 may be printed in a relatively low resolution toensure that the output of each pixel will print clearly. In one aspect,the resolution may be chosen to accommodate the requirements of thefunction T_(E). For example, the reverse bits transformation functioncan only be applied to visible images 42 with dimensions that aredefined by powers of two.

Some visible images 42, i.e., those with a large amount of background orcontent, may appear to have a slight yellow color cast over thebackground region and/or a slight blue color cast over the contentregion. The intensity of this color can be greatly reduced if apredictive coding or other compression procedure is applied to the imagedata before redundant image 44 is printed. For example, the coordinatesof each pixel can be used to predict those of the next pixel and theprediction errors can be encoded as visible content. While the use ofpredictive encoding may confirm the validity of redundant image 44,incorrect values in the predictive image typically affect more than asingle pixel value, which may make it more difficult to restore originalimage 42. In such cases, interpolation and other data processingtechniques may be necessary to restore the values that are alteredthrough predictive encoding.

A redundantly encoded image 55 that has been printed using a system andmethod such as that described can be digitally captured (e.g., scanned)and redundant image 44 can be processed to recreate original image 42.As explained above, in addition to a visible image 57, redundantlyencoded image 55 includes a redundant image 44 that has been printed ondocument 50 in locations that are defined by encoding function T_(E).Original image 42 can be recreated from a digitally captured redundantlyencoded image 55. Generally, present systems and methods apply adecoding transformation function (T_(D)), which is typically the inverseof function (T_(E)) to each pixel in the captured image 54 thatcorresponds to pixel in redundant image 44. A grayscale value that canbe easily detected by the human eye can then be assigned to pixels thatare identified by the decoding transformation function. If none of theinformation printed on document 50 has been modified, visibly presentedimage 57 will be identical to original image 42.

Referring to FIG. 6, registration marks 46 may optionally be printed inredundant image 44 during encoding to aid in recovering visible image42. In one aspect, registration marks 46 may be printed in redundantimage 44 in response to signals that are transmitted over the channel ofprinter 10 that controls the deposit of yellow colorant. In anotheraspect, registration marks 46 may be printed using the cyan, magenta orother color channel. In still another aspect, registration marks 46 maybe printed in redundant image 44 in a predetermined manner, for example,at periodically spaced intervals or at specified locations (e.g.,corners, centers, etc.) within blocks of pixels that have a specifiedsize and shape or are arranged in some other known pattern.

In one aspect, a redundant image 44 that has been encoded using thetransformation function T_(E) with reference to FIG. 5, i.e., (i′,j′)=[i′=reversebits(i+j); j′=reversebits(j+i′)], may be decoded using aninverse transformation function TD(i, j)=[i=reversebits(i′)−j′; jreversebits(j′)−i], where mod operations may be required to confine iand/or j to the image dimensions.

An exemplary method 101 of recovering visible image 42 from an encodedimage 55 printed on a document 50 is shown in the block diagram of FIG.7. Encoded image 55 is digitally captured at block 100 by scanning adocument 50 that has been positioned on platen 32. Since platen 32 willusually accommodate documents 50 that have different sizes, scanned data54 will typically include pixels that represent the backing roll orscanner cover and other scanner hardware as well as document.

IIT 30 may capture images at a resolution that differs from that used toprint encoded image 55. Document 50 may also have become misaligned whenit was placed on platen 32, which may cause scanned image 54 to becomerotated and/or translated relative to encoded image 55. Accordingly, thegeometrical transformation (TG) between the coordinates of pixels inscanned image 54 and the corresponding locations of document 50 is nextidentified at block 200. T_(G) can be used to identify the position ofeach pixel in redundant image 44 within scanned image 54.

Still referring to FIG. 7, at block 300, TD is applied to the pixels inscanned image 54 that correspond to redundant image 44 and determiningwhether a blue or yellow dot has been placed in the correspondinglocation. This mapping can include local adjustments based onexamination of the positions of nearby registration points. If a yellowor blue dot is found in the selected scanned image location, a blackpixel is printed at block 400 in the location obtained through inverseencoding of the current position.

One way to determine transformation T_(G) is illustrated in FIG. 8. Theedges of document 50 are first located inside scanned image 54 at block210 using, for example, one of several known edge detection processes.For example, pixels at the boundaries that lie between regions withdistinct gray-level properties can be identified and the pixelcoordinates can be used to fit lines to the top, bottom, left and rightedges of document 50. More specifically, starting at the top of thescan, the grayscale value for each pixel can be analyzed to until aplurality of non-white pixels are located together. The number of whitepixels that should be analyzed will depend upon the parameters of system10, but should be sufficient to rule out the possibility of noise. Thelocations of these non-while pixels can be entered into a least-squaresfit of a line to the edge and the left-most and right-most non-whitepixels on the line noted. Subsequent lines can then be processed tocapture any non-white pixels that lie outside the previously identifiedrange until the distance between two non-white pixels in a single scanline equals the scanner resolution in the fast scan direction. Theleast-squares fit can then be applied to the collected points to providethe leading edge. An analogous process can be used to fit lines to thebottom, left and right sides.

Once the pixels of scanned image 54 that correspond to the edges ofdocument 50 are identified, function T_(G) is constructed at block 220using the coordinates for pixels of the boundaries identified at block210 and the dimensions of document 50, which are known. Function T_(G)may optionally be refined at block 230 to provide a precise mappingbetween pixels in scanned image 54 and corresponding pixels in encodedimage 55.

A process that can be used to refine a function T_(G) is illustrated inFIG. 9. In the example of FIG. 9, encoded image 55 includes registrationmarks 46 that have been printed at the corners of 16×16 blocks ofpixels. However, it is understood that registration marks may be printedin other patterns and that the main goal is to provide registrationmarks 46 that can be easily printed and captured. Starting with thefirst pixel in the first scan line (blocks 231 and 232), theneighborhood surrounding each pixel in scanned image 54 is analyzed todetermine whether a registration mark is present. More specifically, atblock 233 the grayscale value of the pixel is compared to a thresholdvalue t_(R) that is used to identify registration marks 46. In aredundant image 44 printed in blue and yellow, registration marks willbe found where |B−(R+G)/2|−|R−G|>t_(R).

The neighborhood surrounding each registration mark pixel is thenexamined at block 234 to identify pixels have a higher intensity valuefor the selected color. If any of the surrounding pixels have higherintensity values, their coordinates are entered into a least squares fitat block 235 and T_(G) will be adjusted further. No further adjustmentis made if none of the surrounding pixels have higher intensity values.Processing continues at blocks 236-238 until each pixel in scanned imagehas been analyzed as shown at block 239.

Each adjustment to T_(G) can be used to predict the position of the nextregistration mark 46, which will allow the adjustments to followprogressively drifting errors. The effects of noise in the adjustmentcalculations can be reduced by updating the mapped registration mark 46location with an average of several nearby previously calculatedadjustments, rather than with a single previously adjusted value. Ifdesired, the refined transformation could also be concatenated with theoriginal transformation function (from block 220 of FIG. 8). Any or allof these processes can be repeated to increase the accuracy of thetransformation function.

While present systems and methods are described using redundantlyencoded images 55 as being printed on white paper, with visible image 42printed in black and redundant image 44 printed in blue and yellow, itis understood that redundant image 44 could be printed in other colorsand/or on non-white output sheets. Generally, redundant image 44 will besubstantially invisible so long as the luminance of the colorant used toprint it varies only slightly from the media on which it is printed. Forexample, image data signals may be transmitted over the magenta printchannel to redundantly encode an image 55 on a red output sheet (i.e.,R=255, G=0, B=0; L=76, Cr=255, Cb=86), by printing redundant image 44 inmagenta (i.e., R=255, G=0, B=255; L=105, Cr=234, Cb=212) and printingvisible image 42 in dark green (i.e., R=0, G=128, B=0; L=75, Cr=75,Cb=86).

Although the invention has been described with reference to specificembodiments, it is not intended to be limited thereto. Rather, thosehaving ordinary skill in the art will recognize that variations andmodifications, including equivalents, substantial equivalents, similarequivalents, and the like may be made therein which are within thespirit of the invention and within the scope of the claims.

1. A digital printing system, comprising: an image processor configuredto generate binary printer signals that represent an encoded imageinside a scan image, wherein said encoded image includes a visiblerepresentation of a presented image and has a substantially invisiblerepresentation of an original image printed among said presented image;a print channel configured to receive said binary printer signals fromsaid image processor as a plurality of separations; an encoded imageanalyzer configured to obtain an encoding transformation function usedto position pixels corresponding to said substantially invisibleoriginal image representation among said original image; an originalimage location identifier that identifies pixels in said scan image thatcorrespond to locations of said substantially invisible original imagerepresentation and applies a decoding transformation function to saidsubstantially invisible original image representation correspondingpixels; an original image recovery device configured to assign aselected grayscale value to each pixel of said substantially invisibleoriginal image representation identified by said decoding transformationfunction; and an output generator configured to generate a visiblerepresentation of said original image.
 2. A digital printing system asclaimed in claim 1 wherein said encoded image analyzer is furtherconfigured to position pixels of said substantially invisible originalimage representation at locations that are scrambled relative tocorresponding pixels of said original image.
 3. A digital printingsystem as claimed in claim 2 wherein pixels of said substantiallyinvisible original image representation are defined by coordinates (i′,j′), pixels of said original image are defined by coordinates (i, j),and said original image location identifier is further configured toapply a decoding transformation function defined asi=reversebits(i′)−j′; j=reversebits(j′)−i.
 4. A digital printing systemas claimed in claim 1 further comprising: an image analyzer configuredto detect differences between said presented image and said originalimage; and an image marker configured to generate visible output thathighlights said detected differences.
 5. A method, comprising: digitallycapturing grayscale pixels that represent an encoded image inside a scanimage, wherein said encoded image includes a visible representation of apresented image and has a substantially invisible representation of anoriginal image printed among said presented image; identifying anencoding transformation function used to position pixels correspondingto said substantially invisible original image representation among saidoriginal image; locating pixels in said scan image that correspond tolocations of said substantially invisible original image representation;applying a decoding transformation function to said substantiallyinvisible original image representation corresponding pixels to locatepixels corresponding to said original image; and assigning a selectedgrayscale value to each of said original image corresponding pixels. 6.A method as claimed in claim 5 further comprising: detecting differencesbetween said presented image and said original image; and generatingvisible output that highlights said detected differences.
 7. A method asclaimed in claim 5 digitally wherein presented image is printed bydepositing black colorant on a white sheet of paper and said redundantimage is printed by depositing blue and yellow colorant on said a whitesheet of paper.
 8. A method as claimed in claim 5 further comprisingpositioning pixels of said substantially invisible original imagerepresentation at locations that are scrambled relative to correspondingpixels of said original image.
 9. A method as claimed in claim 8 furthercomprising applying a decoding transformation function defined asi=reversebits(i′)−j′; j=reversebits(j′)−i, wherein pixels of saidsubstantially invisible original image representation are defined bycoordinates (i′, j′) and pixels of said original image are defined bycoordinates (i, j).
 10. A method as claimed in claim 5 wherein saidinput image has a plurality of registration marks positioned therein.11. A method as claimed in claim 5 further comprising decompressing saidsubstantially invisible original image representation.
 12. A datadecoder, comprising: an image sensor configured to capture an inputimage that includes a plurality of substantially invisible elements ofan electronic code as pixels that represent an intensity of lightreflected said input image; a code element locator configured toidentify a plurality of pixels that have a color value that issubstantially different from said average color value for a surroundingneighborhood and a luminance value that is substantially the same as anaverage luminance value for a surrounding neighborhood; a code elementpattern detector configured to detect a layout pattern for saidelectronic code based upon a spatial relationship of said code elementlocator identified pixels; and an electronic code generator configuredto identify input image pixels corresponding to said electronic codepattern and assign output values to said identified electronic codepattern corresponding pixels based upon a dominance of a selected colorof light reflected from said input image.
 13. A method, comprising:generating image data that provides a digital representation of anoriginal image; providing an encoding transformation function forpositioning pixels of a substantially invisible representation of saidoriginal image inside said original image; printing said original imagean output copy sheet; and printing said substantially invisible originalimage representation on said output copy sheet, with pixels of saidsubstantially invisible original image representation dispersed amongsaid original image.
 14. A method as claimed in claim 13, wherein saidoriginal image is printed by depositing black colorant onto a whiteoutput sheet and said substantially invisible original imagerepresentation is printed by depositing blue and yellow colorant ontosaid white output sheet, with yellow colorant deposited on said outputsheet in background region corresponding locations of said visible imageand blue colorant deposited on said output sheet in content regioncorresponding locations of said visible image.
 15. A method as claimedin claim 13 wherein a print resolution of said substantially invisibleoriginal image representation differs from a print resolution for saidoriginal image.
 16. A method as claimed in claim 13 further comprisingcompressing said image data prior printing said substantially invisibleoriginal image representation.
 17. A method as claimed in claim 13wherein pixels in said original image are dispersed among correspondingpixels of said substantially invisible original image representationusing to the function: j′ reversebits(i+j); i′=reversebits(j′+i),wherein (i, j) are the coordinates of said original pixels and (i′, j′)is are the coordinates for corresponding pixels in said substantiallyinvisible original image representation.
 18. A data encoder, comprising:an input channel configured to receive pixel values that digitallyrepresent an original image; a redundant image pixel selector configuredto provide an encoding transformation function that maps pixelsbelonging to a substantially invisible representation of said originalimage to corresponding pixels in a visible representation of saidoriginal image; a visible image generator configured to print saidvisible original image representation on an output copy sheet using acolorant whose luminance value differs substantially from a luminancevalue of a print location for said visible image representation; and aredundant image generator configured to print said substantiallyinvisible original image representation using a colorant whose luminancevalue is substantially the same as a luminance value for a pixelidentified by said encoding transformation function.
 19. A data encoderas claimed in claim 18, wherein said visible image generator isconfigured to deposit black colorant onto said output sheet and saidredundant image generator is configured to print yellow colorant in avisible image background region of said output sheet and is configuredto print blue colorant in a visible image content region of said outputsheet.
 20. A data encoder, comprising: an input channel configured toreceive pixel values that digitally represent an original image; aredundant image pixel selector configured to provide an encodingtransformation function that maps pixels belonging to a substantiallyinvisible representation of said original image to corresponding pixelsin a visible representation of said original image; a visible imagegenerator configured to visibly display said visible original imagerepresentation in color whose luminance value differs substantially froma luminance value of a region surrounding said visible imagerepresentation; and a redundant image generator configured to displaysaid substantially invisible original image representation in a colorwhose luminance value is substantially the same as a luminance value ofa surrounding location.